{"id":"W6913206175","doi":"10.5683/sp3/zf6x3f","title":"SEEDNet Library","year":2024,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"","keywords":"Demographics; Data collection; Epidemiology; Information system","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001175951,0.0004509193,0.0004000965,0.0004377553,0.00003883367,0.0003415948,0.0009111128,0.0004752438,0.002295685],"category_scores_gemma":[0.00005064128,0.0004039543,0.0001896896,0.0004447968,0.00008743285,0.0002441182,0.0005180966,0.0006996,0.11387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005754902,"about_ca_system_score_gemma":0.0002849914,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01971663,"about_ca_topic_score_gemma":0.005331138,"domain_scores_codex":[0.9981385,0.00008082685,0.0003113133,0.0005948132,0.0004682156,0.0004062733],"domain_scores_gemma":[0.9980956,0.00005455601,0.0001146506,0.001517516,0.00001642807,0.0002012652],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001587304,0.00003600532,0.000001327291,0.000275753,0.000131373,0.0006843013,0.00001052154,3.965841e-7,0.000001382107,0.00007218746,0.9987015,0.0000693468],"study_design_scores_gemma":[0.0000863448,0.00002560458,0.00004473573,0.0001967677,0.0002740895,0.00003647215,0.000006100992,0.000003195683,0.00001159788,0.0005915077,0.998274,0.0004495527],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[1.531117e-7,0.001171221,3.498477e-8,0.000249585,0.0004354584,0.0002207953,0.9800785,0.0008481342,0.01699617],"genre_scores_gemma":[5.075099e-8,0.0003027908,0.0000458282,0.0006334004,0.001466233,0.00006013169,0.9955343,0.0003053423,0.001651911],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1115743,"threshold_uncertainty_score":0.9998412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01489297389635856,"score_gpt":0.2581758456030808,"score_spread":0.2432828717067222,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}